Causal relationship between systemic circulatory inflammatory regulators and intervertebral disc degeneration: A bidirectional 2-sample Mendelian randomization study.

In the context of the development of intervertebral disc degeneration (IDD), inflammatory mediators play a pivotal role. Nevertheless, due to the influence of the inflammatory microenvironment, the causal relationship between specific inflammatory mediators and the development of IDD remains uncertain. The understanding of the causal relationship between inflammatory mediators and IDD is of great importance in preventing and delaying disc degeneration in the future.

[Comparsion of bone setting technique combined with percutaneous vertebroplasty and percutaneous kyphoplasty for the treatment of osteoporotic vertebral compression fractures].

Objective: To explore clinical efficacy of osteoplasty combined with percutaneous vertebroplasty(PVP) and percutaneous kyphoplasty (PKP) alone in treating osteoporosis vertebral compression fractures (OVCFs).

Methods: The clinical data of 80 patients with single-level OVCFs treated from January 2021 to June 2022 were retrospectively analyzed, and were divided into treatment group and control group according to different surgical methods, 40 patients in each group. In treatment group, there were 24 males and 16 females, aged from 60 to 83 years old with an average of (70.

A combined radiomic model distinguishing GISTs from leiomyomas and schwannomas in the stomach based on endoscopic ultrasonography images.

Background: Endoscopic ultrasonography (EUS) is recommended as the best tool for evaluating gastric subepithelial lesions (SELs); nonetheless, it has difficulty distinguishing gastrointestinal stromal tumors (GISTs) from leiomyomas and schwannomas. GISTs have malignant potential, whereas leiomyomas and schwannomas are considered benign.

Purpose: This study aimed to establish a combined radiomic model based on EUS images for distinguishing GISTs from leiomyomas and schwannomas in the stomach.

Autoimmune pancreatitis: A bibliometric analysis from 2002 to 2022.

Background/objectives: Autoimmune pancreatitis (AIP) is a distinct form of pancreatic inflammatory disease that responds well to glucocorticoid therapy. Knowledge on AIP has rapidly evolved over the past two decades. Based on bibliometric analysis, this study aimed to assess the research status of AIP over the past two decades and determine the research focus and emerging topics.

Pseudoileus caused by primary visceral myopathy in a Han Chinese patient with a rare mutation: A case report.

Background: Chronic intestinal pseudo-obstruction (CIPO) is a syndrome of intestinal motor dysfunction caused by intestinal nerve, muscle, and/or Cajal stromal cell lesions. CIPO is a serious category of gastrointestinal dynamic dysfunction, which can eventually lead to the death of patients with intestinal failure. Due to considerable phenotypic heterogeneity, the estimated incidence of CIPO is 1/476190 and 1/416666 in men and women, respectively.

Deconvolution of sparse underwater acoustic multipath channel with a large time-delay spread.

The deconvolution of multipath underwater acoustic channel with a large time-delay spread is investigated. The channel deconvolution involves estimating the multipath time-delays and attenuation factors from a noisy received signal consisting of multiple overlapped signals. Similar to conventional deconvolution methods, the proposed method estimates channel impulse response based on least-squares criterion.

A neural network learning for adaptively extracting cross-correlation features between two high-dimensional data streams.

This paper proposes a novel cross-correlation neural network (CNN) model for finding the principal singular subspace of a cross-correlation matrix between two high-dimensional data streams. We introduce a novel nonquadratic criterion (NQC) for searching the optimum weights of two linear neural networks (LNN). The NQC exhibits a single global minimum attained if and only if the weight matrices of the left and right neural networks span the left and right principal singular subspace of a cross-correlation matrix, respectively.